2  Spatial and Temporal Emergence Timing of Young-of-Year (YOY) Brook Trout (Salvelinus fontinalis)

3 Abstract

Brook trout (Salvelinus fontinalis)is a cold-water species native to streams of Eastern North America whose populations often exhibit significant year-to-year variation in body size. Previous research has found that this variation is related to environmental variables like stream flow and water temperature, but less is known about the biological mechanisms driving these patterns. In particular, temperature-mediated timing of early life events (spawning, hatching, and emergence) may underlie spatial, temporal, and among-individual variation in Young-of-Year (YOY) body size. Early emerging individuals have more time to grow than late-emerging individuals and may, therefore, gain a size-based competitive advantage, but this could come at the cost of greater exposure to early-season environmental stressors such as higher flows, colder temperatures, and lack of food (in addition to increased predation risk). To understand how emergence phenology mediates the effect of temperature on Brook Trout population dynamics, finer-scale research is needed on emergence patterns across years, streams, and individuals. To address this, from 2014 to 2023, we carried out a field study in six headwater streams across Western Massachusetts, exploring the relationship between YOY brook trout emergence and environmental variables (stream flow and temperature). We combined direct (periodic dip-net surveys to monitor for the presence of YOY) and indirect (back-calculating emergence date based on ages estimated from otoliths) techniques to estimate the emergence timing of YOY brook trout. Preliminary results indicate wide variation in emergence timing within the streams, among streams, and between years. We tested the degree to which year-to-year differences could be predicted by both water temperatures and spawn timing. Data on emergence timing will help assess its effect on the body size distribution of YOY and early life survival, especially considering the threats posed by an increase in high-flow events during their most vulnerable periods.

4 Introduction

5 Questions

1. Is there a spatial and temporal variation in emergence timing within and among streams?
2. If there is a variation how well can temperature predict it?

6 Methods

6.1 Study Site Locations

The study was conducted at six first- and second-order streams within the Connecticut River Watershed in Western Massachusetts, USA, between 2014 and 2015. Because we were researching if there was an effect of temperatur on the emergence timing of YOY brook trout, streams across a wide temperature spectrum were chosen. Eight potential study sites were compiled from a study on adult brook trout’s upper thermal tolerance limit. The dip-net technique assessed each site for the presence of young-of-the-year (YOY) brook trout. The two sites with minimal or no YOY brook trout were excluded. Six were selected from the eight streams studied.

From north to south, Four Mile Brook, located in Northfield, Massachusetts, is a low-gradient second-order headwater stream with a substrate composed of boulders and cobble. Pond Brook, whose substrate consists of sand and gravel, is a low-gradient headwater stream in Montague, Massachusetts. The next three streams are located within the West Brook Watershed, a small third-order stream in Whately, Massachusetts. West Whately Brook is a low-gradient headwater stream with a substrate made of sand and gravel. Sanderson Brook is a high-gradient second-order headwater stream with a substrate of cobbles and boulders. O’bear Upper Brook is a high-gradient first-order headwater stream with an average width smaller than that of Sanderson Brook but with a similar substrate. In Montgomery, Massachusetts, is a stream named Roaring Brook, whose substrate is dominated by large boulders and bedrock.

After selecting the study streams, we standardized the ideal dip netting habitats across all sites. Capturing young-of-the-year (YOY) fish is more effective in calm, shallow waters near the stream banks, previously identified as YOY habitats (Hayden personal observation). These tranquil areas also provide clear visibility for observers. Attempting to make each study stream the same length proved ineffective, as more significant streams also contain YOY habitats in the middle and along the banks. Therefore, we used the total wetted area to ensure that each study site was comparable. Yellow-capped rebar stakes were used to mark the upstream and downstream boundaries of all study locations sites. Stream temperature was recorded every 15 minutes using Hobo Pro v2 temperature loggers (Model U22-001; Onset Computer Inc., Bourne, MA, USA), which were cable-tied to trees in PVC housing.

Map

Figure 6.1: Interactive table of all the six YOY study streams

Table

Figure 6.2: Interactive table of all the six YOY study streams

6.2 Emergence Estimation

6.2.1 Direct (Dip Net / Electrofisher )

The sampling season was split into two parts to effectively collect data on the body size distribution during the first six months of the brook trout YOY life cycle. It comprised dipnet sampling in the spring and two electrofishing samples in the summer and fall. Initially, from March to July, the trout experienced rapid growth; this was followed by a notable slowdown from June to October. In late January, the researcher visited each stream weekly and checked the slack water of each study stream to check for the presence of newly emerged YOY. When emergence began, the researcher continued to visit the stream, using dip nets, and attempted to catch every YOY trout in the study section. YOY was measured for fork length and released into the stream. When the YOY could not be effectively captured using dip-nets, each study stream was electrofished once in the summer and once in the fall. Each study site was divided into three sections: 40 m, one at the downstream end, one in the middle, and one at the upstream end. Brook trout adults and juveniles were captured using a backpack electrofisher, measured for fork length, and returned to the section they were caught in.

All data were entered into an Excel file and loaded into R (Team 2008). An upper, middle, and lower quantile regression was utilized to calculate the beginning, middle, and end of emergence. When the juvenile Brook Trout data were graphed by fork length and detection date, it was noted that the size distribution increased at the same rate for the first two to four samples, then leveled off for the remaining samples (Figure 6.2). It was hypothesized that the distribution leveled off not because of a decrease in growth, but due to a reduction in capture probability as fry size coincided with an increase in speed. The researcher could see larger YOY but was unable to capture them. It was assumed that the slope of this line could be used to calculate the date when the size distribution correlated with the start of emergence. The beginning of emergence was hypothesized to occur when the maximum and minimum size distributions were the same, which may be 19mm for two reasons. First, the smallest size of YOY was observed during the dip net samples. Second, the size of a newly hatched Brook Trout for the 2014 thermal tolerance study was between 12-18mm (Letcher, B.H., Odonnell, M.J., Unpublished Data).

The end of emergence was determined using the same theory. Throughout the emergence period, the size distribution maintained a consistent minimum of 19 mm ± 1. A change in this pattern corresponded with the end of emergence. A lower quantile (0.02) regression was employed to calculate the date when emergence concluded. The middle or peak of emergence utilized the same method as the start and end, with linear regression applied instead of quantile regression.

The data were first filtered to include all juvenile Brook Trout captured from the dip net and the initial electrofishing samples. Next, the data were organized by river and year to calculate the start of emergence and an upper quantile regression was conducted for each nested data frame. The data were un-nested, and the slope and intercept from each quantile regression were utilized to determine the day of the year when the line intersected a fork length of 19 mm, representing the emergence size. The emergence calculation method was reiterated for the middle quantile. To enhance end-of-emergence calculations, the data for the lower quantile models were filtered to exclude the initial few samples. If the first few samples were retained, the quantile’s estimate for the emergence end would have occurred earlier.

Figure 6.3: Relationship of body size over time for Pond Brook during the 2015 spring dip-net and electrofishing sample. An example of how the body size distributions over days of the year can be used to calculate emergence timing. The three lines represent the upper (red) , middle (orange) , and lower (green) quantile regression.

6.2.2 Indirect (Otolith)

Fish were collected for otoliths, once during the dip-net sample and once during each electrofishing sample. For the dip net sample collection, seven weeks after emergence began at an individual site, six fish were collected, representing the body size distribution measured in fork length. During the summer and fall electrofishing samples, nine fish were taken at each study site, representing the full body size distribution. Fish collected for otolith analysis were placed in individual bags, each labeled with the fish’s fork length, stream, and date killed. The bags were then placed in a freezer.

7 Results

7.1 Question 1

Is there a spatial and temporal variation in emergence timing within and among streams?

All Emergence

Temporal Variation

Spatial Variation

Spatial and Temproal Variation Combined

7.1.1 Spatial and Temporal Variation Emergence (Start, Middle, End)

7.2 Question 2.

• There is spatial and temporal variation in emergence timing within and among sites.

• To what degree does mean daily stream temperature influence the spatial and temporal variation in emergence timing within and among sites.

7.2.1 Spatial and Temporal Variation in Temperature accross rivers

Spatial Variation Water Temperature ( Average Day/Stream )

Temporal Variation Water Temperature ( Average Day/Stream )

Spatial and Temporal Variation Water Temperature ( Average Day/Stream )

7.2.2 Maximum Cumulative Degree Days ( Spatial and Temporal )

7.2.3 Predicted Emergence (Otolith) vs Observed Emergence (Dip Net)

7.2.4 Stream Temperature vs Dip Net Estimated Emergence (By Site)